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The A18 scores higher than the A16 Bionic in the cited CPU and graphics benchmarks, but the size of the lead depends on the test and the iPhone being measured. Geekbench’s current device averages put the iPhone 16 ahead of the iPhone 15 in both single-core and multi-core scores; other published comparisons show the same direction. These are device-level results, not controlled tests of the chips in identical conditions, so they do not predict an equal percentage improvement in every app, game, or battery-life scenario.

Which iPhones use the A18 and A16 Bionic?

Apple’s iPhone 16 technical specifications identify the iPhone 16 as an A18 device. Geekbench’s device chart also lists the iPhone 16 Plus and iPhone 16e under A18. For the A16 Bionic, Geekbench lists the iPhone 15 and iPhone 15 Plus; Apple’s iPhone 14 Pro technical specifications provide an official reference for an earlier A16-era phone.

These host-device examples matter because benchmark results reflect the phone as well as its processor. Also, not every chip called “A16” should be treated as the A16 Bionic: Geekbench’s chart lists the 11th-generation iPad as using Apple A16, a distinct listing from the iPhone 15-family A16 Bionic entries.

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Geekbench 7: iPhone 16 vs iPhone 15 averages

Geekbench’s iOS Benchmarks chart shows user-submitted Geekbench 7 results, and includes a device only after at least five unique results. In the visible chart, the iPhone 16 (A18) has higher average scores than the iPhone 15 (A16 Bionic):

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Device and chip Geekbench 7 single-core Geekbench 7 multi-core
iPhone 16 (A18) 2,798 7,585
iPhone 15 (A16 Bionic) 2,252 5,967

These are chart averages for the named phones, not a controlled chip-only comparison. The chart says higher scores are better and that doubling a score represents double performance on Geekbench’s calibrated scale. That does not mean an app will run twice as fast, or that a particular score gap translates directly into the same improvement in day-to-day use.

How other benchmark comparisons differ

Other sources also report higher A18 results, but their scores should be read in the context of the benchmark version, sample, and device used.

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NanoReview’s comparison aggregates

NanoReview’s A18 vs A16 Bionic comparison reports the following benchmark values. The visible sample counts differ between chips, so these are aggregator snapshots rather than results from identical, controlled test groups.

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Test A18 A16 Bionic Reported test counts (A18 vs A16)
Geekbench 6 single-core 3,431 2,631 6 vs 24 CPU tests
Geekbench 6 multi-core 8,638 6,602 6 vs 24 CPU tests
Geekbench 6 GPU Compute 28,010 22,851 4 vs 12 GPU tests
AnTuTu 11 total 1,972,476 1,626,008 29 vs 36 tests

One published iPhone 16 and iPhone 15 test

In a device-level report published by GIGAZINE on September 21, 2024, an iPhone 16 scored 3,213 single-core and 7,786 multi-core in Geekbench 6, compared with 2,601 and 6,452 for an iPhone 15. The reported Metal GPU scores were 27,974 for the iPhone 16 and 22,968 for the iPhone 15. These are measurements from the reported devices, not a lab-controlled comparison of isolated chips. The report also includes Geekbench AI results; those figures should not be read as a universal measure of AI performance.

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What the specifications suggest—and what they do not

NanoReview’s specification table lists both chips with six-core CPUs, five-core GPUs, and 16-core Neural Engines. It lists theoretical Neural Engine performance at 35 TOPS for A18 and 17 TOPS for A16 Bionic. These figures are specifications reported by NanoReview, not an Apple chip datasheet cited here, so treat them as attributed comparison-table values rather than independently verified measurements.

Core counts alone do not establish how quickly a particular app runs. The benchmark evidence supports a narrower conclusion: the cited A18 iPhone results lead the cited A16 Bionic iPhone results in CPU and graphics tests. It does not establish a controlled battery-life comparison or sustained-thermal comparison between comparable phones, nor does it show that performance differences remain constant during long workloads.

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How to use the comparison when choosing a phone

  • For benchmark performance: the cited results favor A18, including Geekbench CPU scores and graphics/compute measurements.
  • For everyday speed: benchmark gaps are useful indicators, not direct forecasts of how much faster every task will feel. App, workload, software, and device conditions matter.
  • For gaming or long heavy workloads: the sources provide graphics benchmark snapshots, but not controlled sustained-performance or thermal comparisons.
  • For battery life: these scores do not establish which phone lasts longer. No independent controlled battery-life comparison is included in the evidence cited here.
  • For used or refurbished options: compare the specific phone’s condition, price, and support situation separately from its chip benchmark. The results alone cannot establish the value of a particular listing.

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